Purpose <p>This study aimed to investigate the association between the change ratios of nutritional indicators and the efficacy of neoadjuvant chemoradiotherapy (nCRT) and survival in patients with locally advanced rectal cancer (LARC).</p> Methods <p>This study comprised 208 LARC patients with serial measurements of nutritional indicators including red blood cell count (RBC), hemoglobin (HB), platelet count (PLT), prognostic nutritional index (PNI), and body mass index (BMI). Stratification by pathological response was followed by Cox regression modeling for survival analysis (DFS/OS) and logistic regression for nCRT response prediction. The receiver operating characteristic (ROC) curves were used to measure the prediction power of the independent nutritional markers.</p> Results <p>Multivariate logistic regression analysis confirmed RBC and HB were independent predictors for the efficacy of nCRT. RBC and HB were used to predict the area under the ROC curve of the efficacy of nCRT, which was greater than the single indicator prediction of the change ratio of RBC or HB. Multivariate Cox regression analyses revealed that HB was significantly associated with DFS and OS in LARC patients.</p> Conclusion <p>RBC and HB independently predicted the efficacy of nCRT and HB was significantly associated with DFS and OS in patients with LARC. Patients maintaining optimal nutritional parameters throughout the treatment exhibited significantly improved nCRT response rates and survival outcomes.</p>

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Nutritional indicators as predictive and prognosis biomarkers for neoadjuvant chemoradiotherapy outcomes in patients with locally advanced rectal cancer

  • Zhenyong Shao,
  • Yihe Zou,
  • Changlin Zou,
  • Yuyan Xu

摘要

Purpose

This study aimed to investigate the association between the change ratios of nutritional indicators and the efficacy of neoadjuvant chemoradiotherapy (nCRT) and survival in patients with locally advanced rectal cancer (LARC).

Methods

This study comprised 208 LARC patients with serial measurements of nutritional indicators including red blood cell count (RBC), hemoglobin (HB), platelet count (PLT), prognostic nutritional index (PNI), and body mass index (BMI). Stratification by pathological response was followed by Cox regression modeling for survival analysis (DFS/OS) and logistic regression for nCRT response prediction. The receiver operating characteristic (ROC) curves were used to measure the prediction power of the independent nutritional markers.

Results

Multivariate logistic regression analysis confirmed RBC and HB were independent predictors for the efficacy of nCRT. RBC and HB were used to predict the area under the ROC curve of the efficacy of nCRT, which was greater than the single indicator prediction of the change ratio of RBC or HB. Multivariate Cox regression analyses revealed that HB was significantly associated with DFS and OS in LARC patients.

Conclusion

RBC and HB independently predicted the efficacy of nCRT and HB was significantly associated with DFS and OS in patients with LARC. Patients maintaining optimal nutritional parameters throughout the treatment exhibited significantly improved nCRT response rates and survival outcomes.